1 Course Description

This course provides an introduction to the R programming language and software environment for statistical computing and graphics. A variety of examples with a biological theme will be presented.

Although this is created based on class-sessions in mind, it can also adopted as self-learning material.

2 Prerequisites

No prior programming experience is required, but those attending should be able to use a plain text editor. A very basic knowledge of UNIX would be an advantage, but nothing will e assumed and extremely little will be required.

3 Objectives

After the course you should feel confident to start exploring your own dataset using the materials and references provided. Including things like:

  • Import data and plot graphs
  • Perform statistical tests in R
  • Create a documented and reproducible piece of R code
  • Know how to develop your skills in R after the course
  • Install and use Bioconductor packages

4 Aims

During this course you will learn about:

  • The R Studio interface to R
  • The many ways to access help about R
  • Basic object types in R
  • Importing tabular data into R
  • Manipulating data in R
  • Using in-built functions
  • Statistical testing in R
  • Executing basic data analysis workflows in R
  • Basic Plotting
  • Customizing plots
  • Basic programming with if/else statements and for loops
  • Creating reproducible reports in R

5 Course Structure

6 Resources:

This materials are combination of one or more resources listed bellow.123

  1. Cambridge Basic R Course↩

  2. swcarpentry r-novice-inflammation↩

  3. few others↩

 

Created and Maintained by Sangram Keshari Sahu
Licensed under CC-BY 4.0
Source Code At GitHub
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